Transformation | Compute rigid transformation and similarity transformation | 3D Printing library

I have a data frame which I need to transform. I need to change the unique rows into single columns based on the value of a column.

My data below:

I am working on a large Pandas DataFrame which needs to be converted into dictionaries before being processed by another API.

The required dictionaries can be generated by calling the .to_dict(orient='records') method. As stated in the docs, the returned value depends on the orient option:

Returns: dict, list or collections.abc.Mapping

Return a collections.abc.Mapping object representing the DataFrame. The resulting transformation depends on the orient parameter.

For my case, passing orient='records', a list of dictionaries is returned. When dealing with lists, the complete memory required to store the list items, is reserved/allocated. As my dataframe can get rather large, this might lead to memory issues especially as the code might be executed on lower spec target systems.

I could certainly circumvent this issue by processing the dataframe chunk-wise and generate the list of dictionaries for each chunk which is then passed to the API. Furthermore, calling iter(df.to_dict(orient='records')) would return the desired generator, but would not reduce the required memory footprint as the list is created intermediately.

Is there a way to directly return a generator expression from df.to_dict(orient='records') instead of a list in order to reduce the memory footprint?

I've built this new ggplot2 geom layer I'm calling geom_triangles (see https://github.com/ctesta01/ggtriangles/) that plots isosceles triangles given aesthetics including x, y, z where z is the height of the triangle and the base of the isosceles triangle has midpoint (x,y) on the graph.

What I want is for the geom_triangles() layer to automatically provide legend components for the height and width of the triangles, but I am not sure how to do that.

I understand based on this reference that I may need to adjust the draw_key argument in the ggproto StatTriangles object, but I'm not sure how I would do that and can't seem to find examples online of how to do it. I've been looking at the source code in ggplot2 for the draw_key functions, but I'm not sure how I would introduce multiple legend components (one for each of height and width) in a single draw_key argument in the StatTriangles ggproto.

Let's say I've got a dataframe with multiple columns, some of which I want to transform. The column names define what transformation needs to be used.

I am a bit stuck, I have a working function that can be utilised using .apply(), however, I cannot seem to get it to work with .assign(). I'd like this to work with assign, so I can chain a number of transformations together.

Could anyone point me in the right direction to resolving the issue?

This works

I'm looking for a way to have all keys / values pair of a nested object.

(For the autocomplete of MongoDB dot notation key / value type)

I was trying to find the source for a certain kind of inlining that happens in GHC, where a function that is passed as an argument to another function is inlined. For example, I may write a definition like the following (using my own List type to avoid rewrite rules):

I have a complex nested dictionary structured like this:

I'm running the test